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Using Artificial Intelligence (AI)-Assisted Pulse Diagnosis Analysis on Precision Critical Medicine.

NCT04675424 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 45

Last updated 2023-09-21

No results posted yet for this study

Summary

Precision/personalized medicine becomes an important part of modern medical system in the recent years. In the past, the treatments for patients have been decided by doctors according patients' symptoms and/or regular biochemical profiles. However, it is not uncommon that patients' condition varies tremendously even they have same diagnosis, and under such condition, treatment efficacy may be limited due to the heterogeneity among patients. Therefore, lack of therapeutic efficacy may be not really ineffective, and the main reason may be inadequate patient classification. For this reason, the "omics"-based personal/precision medicine emerges recently and becomes more and more important. However, in contrast to feasible and common "personalized" medicine, the approach of precision medicine to the molecular medicine level is still difficult, especially among patients in intensive critical units (ICUs). In contrast to cancer, which has remarkable advances in the past decades, the precision/personal medicine is more difficult in critical and emergent medicine. One reason is the amount of omics data is quite huge and thus dealing with omics data is time consuming. Therefore, it is not effective in daily clinical practice in ICUs care. For this condition, the investigators propose that the combination of clinical data, including pulse diagnosis by traditional Chinese medicine (TCM) doctor or ANSwatch wrist sphygmomanometer, fluid responsiveness by "Masimo" Radical-7 Pulse CO-Oximeter, and the specific database from monitors in ICUs may be a feasible way to predict outcome among ICU patients. There are two main goals for this study: (1) After establishing clinical traditional Chinese medicine (TCM) pulse diagnosis and ICU clinical parameters databases, acquiring and features of pulse diagnosis by applying AI and (2) analyzing the correlations between the features of pulse diagnosis and important clinical parameters.

Conditions

  • ICU Patients
  • Shock

Interventions

DEVICE

ANSwatch

ANSwatch wrist sphygmomanometer and the specific database from monitors in ICUs may be a feasible way to predict outcome among ICU patients. Two measurements will be obtained: 1. Pulse diagnosis: Pulse diagnosis done on radial artery is recorded by traditional Chinese medicine physician and ANSwatch wrist sphygmomanometer at the same time. 2. Heart rate variability: Heart Rate Variability represents significant information on autonomic nervous system (ANS)'s regulating function and balance status.

Sponsors & Collaborators

  • Chang Gung Memorial Hospital

    lead OTHER

Eligibility

Min Age
20 Years
Max Age
80 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2020-11-15
Primary Completion
2022-09-06
Completion
2022-10-06

Countries

  • Taiwan

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04675424 on ClinicalTrials.gov